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Solution · Other solutionsThe renewal date reaches the account manager before the customer raises it
Renewals surfaced in Teams and a CRM cleaned every night
A nightly job checks the CRM against rules your sales organisation owns, sends one-click proposals to record owners in Teams, and pushes every approaching renewal to its owner and manager.
Executive summary
Renewals surface when the customer mentions them, and the pipeline is tidied only before the quarterly review.
We start with rules rather than AI. With revenue operations we write down what the CRM is checked against every night: close dates in the past.
Renewals are worked from ninety days out, because the alert reaches owner and manager instead of waiting for the customer to mention the date.
Microsoft Dynamics 365 Sales, written back under a scoped integration user; the change log; Microsoft Power BI
Business problem
CRM
Sellers are paid to sell, not to maintain records. Every field they complete is time not spent with a customer, so fields stay empty, close dates get pushed a month at a time, and the account created on a phone in a car duplicates one that exists. Revenue operations cleans up before every quarterly review with an export, some formulas and a round of emails asking whether a deal is still live. The pipeline is briefly accurate, then decays again.
Renewals fare worse, because nothing forces them to the surface. A renewal date sits in a field no report reads, or in a spreadsheet belonging to one person, so the customer usually raises it first. By then the initiative has moved to their procurement team, and the conversation starts from price rather than value.
Sellers, meanwhile, cannot get a simple answer out of the CRM without clicking through five screens, so they ask sales operations in Teams, which creates a second queue of forty questions a week. It all persists because every fix is a campaign rather than a system: clean-up is periodic, data quality is nobody's day job, and the incentives point away from maintenance.
How it works today
- PersonA seller creates an opportunity, sometimes on a duplicate account, leaving forecast fields estimated or empty
- WaitingThe close date passes and is pushed by a month, then another, without anything challenging it
- PersonBefore the quarterly review, revenue operations exports the pipeline and emails sellers lists of stale records
- PersonSome records are updated, some ignored, a few disputed; the director then adjusts the number by judgement in a separate file
- PersonA seller messages sales operations in Teams for the status of an account before a call, and waits
- Risk of errorA renewal date arrives unnoticed because no report reads the field, and the customer raises it first
Why the current process costs more than it appears
Behind every exception is an hour nobody logged.
- A forecast wrong by a third steers hiring, cash planning and board expectations in the wrong direction, and the error is never traced back to the records it came from.
- Missed renewal windows hand the initiative to the customer's procurement team. A renewal negotiated late is negotiated on price, and that margin does not return the following year.
- Duplicate accounts split the history, so a seller walks into a meeting without knowing a colleague lost a deal at the same company last year.
- Commission calculations, territory planning and marketing attribution inherit the same errors, and each produces its own argument at quarter end.
- New sellers ramp slowly on accounts they cannot trust, and any scoring or forecasting tool bought later will learn confidently from the same noise.
Cost of inaction
Records decay faster than campaigns can repair them, and the gap widens with every hire. Each month adds opportunities, accounts and contacts, and every seller who leaves abandons records nobody re-owns, so each review starts from a worse position than the last. As the company grows, larger decisions rest on the same base: headcount, cash, what the board is told.
Renewal misses compound in a way the table cannot show. A customer not contacted before the renewal date learns that they hold the timing, and negotiates from there again next year. Meanwhile sales operations spends more of its capacity as a help desk, and the number on the slide keeps moving for reasons nobody can explain, which is slower and more expensive than any row above.
A plausible organisation with realistic proportions. The figures are there to be recalculated on your data; they are not a client result.
A business-software and services company with 380 employees selling in five European countries through 46 sellers and account managers, on Microsoft Dynamics 365 Sales with Microsoft Teams as the daily tool.
31,000 accounts, 6,200 open opportunities and 1,100 contracts carrying a renewal date. Three people in revenue operations prepare the pipeline reviews and answer roughly forty status questions a week in Teams. Contracts are signed electronically and kept on SharePoint; invoicing runs in Microsoft Dynamics 365 Business Central.
Clean-up happens before each quarterly review, by export and email. The forecast is assembled in Excel from a CRM extract and adjusted by regional managers. Renewal dates sit in a field nobody reports on, and in at least one spreadsheet.
About 55 minutes a week per seller across lookups, questions to sales operations and pre-review tidying, plus 60 hours a month of revenue-operations time on exports, chasing and corrections.
A nightly robot applies the hygiene rules the sales organisation owns, corrects what the rules call safe and proposes the rest to the record owner on a card in Teams. A second job pushes every renewal inside the alert window to its owner and manager, and a conversational agent answers renewal and account questions from live CRM data.
In the modelled case renewals are worked from ninety days out rather than discovered, the pipeline the sales director presents is the one they believe, and the review discusses deals instead of data. Illustrative figures, not a result.
Proposed solution
We start with rules rather than AI. With revenue operations we write down what the CRM is checked against every night: close dates in the past, mandatory fields missing at forecast stages, accounts with no activity for an agreed period, contracts crossing the renewal window, and the duplicate signals your team already recognises. The rules are a document your sales organisation owns; the robot only executes them.
A UiPath robot runs them nightly through the Microsoft Dynamics 365 CRM connector. Anything inside an agreed safe-change boundary, formatting, standard values, rule-based territory assignment, is applied and written to a change log with the rule behind it. Everything else becomes a proposal on an Adaptive Card in Teams addressed to the record owner: merge these two accounts, confirm or move this close date, complete these three fields. The seller accepts, rejects or edits in one click, on a phone if that is where they are, and the CRM records it under their own identity.
Renewals get their own job. Every contract entering the alert window produces a card to the owner and their manager, with the last activity, the value at stake and the open items; a missing renewal date becomes a proposal in its own right. Alongside it, a UiPath conversational agent published to Microsoft Teams answers what now goes to sales operations: what is open with this account, which of my renewals fall in the next ninety days, what changed here this week. It reads live CRM data through the same connector under the seller's own entitlements, and the only generative step is a summary of activity notes through UiPath GenAI Activities, governed by the AI Trust Layer. Every date, amount and field value in an answer is a record. Power BI then shows a hygiene score per team next to the pipeline.
UiPath Integration Service connectors for Microsoft Dynamics 365 CRM and Microsoft Teams; UiPath Orchestrator time triggers, credential store and job audit; Adaptive Cards through the Workflows app in Microsoft Teams (Power Automate); UiPath conversational agents published to Microsoft Teams; UiPath GenAI Activities under the UiPath AI Trust Layer
The hygiene rule set and its thresholds, the safe-change boundary, the nightly job and its change log, the proposal cards and their one-click responses, the renewal alert job, the agent's CRM tools and guardrails, the Power BI hygiene score
Microsoft Dynamics 365 Sales reads and writes through the Integration Service connector under a scoped integration user; contract metadata from SharePoint where renewal terms live outside the CRM; the same rules ported to Salesforce where that is the CRM
How the automated process works
- AutomationA nightly job reads yesterday's new and changed records and applies the agreed hygiene rules
- SystemCorrections inside the safe-change boundary are written back, each with its rule in the change log
- PersonEverything else reaches the record owner as a card in Teams: merge, confirm the date, complete these fields
- AutomationAccepted proposals are written to the CRM under the seller's own identity; rejections are logged with a reason
- AutomationContracts entering the renewal window produce a card to owner and manager, with value, last activity and open items
- PersonA seller asks the Teams agent what is open on an account or which renewals fall in the next quarter
- AutomationThe agent answers from live CRM data, summarising activity notes where that helps, and names the record it read
- AutomationThe hygiene score per team refreshes in Power BI beside the pipeline it belongs to
Human-in-the-loop model
Automation handles
- The nightly checks for stale dates, missing fields, inactivity, duplicate signals and approaching renewals
- Corrections inside the safe-change boundary, logged and reversible
- Proposal and renewal cards to owners and managers, plus reminders
- Answers to routine account, renewal and change questions in Teams
People decide
- Every merge, close-date change and field value proposed to them
- Forecast judgement on stage and probability, which no rule replaces
- Renewal strategy, timing and price
- The rule set: what is safe, what must be proposed, where the thresholds sit
Before and after
Systems and integrations
The stack is deliberately short: one engine, one execution layer, one place where a person decides.
Inputs
- Microsoft Dynamics 365 Sales records
- contract metadata on SharePoint
- renewal windows and thresholds agreed with revenue operations
Automation layer
- UiPath Orchestrator
- UiPath Robots
- UiPath Integration Service
- UiPath Agents
Target systems
- Microsoft Dynamics 365 Sales, written back under a scoped integration user
- the change log
- Microsoft Power BI
Human touchpoints: proposal cards in Microsoft Teams; renewal cards to owner and manager; the agent conversation
Technologies used
reads and writes accounts, opportunities and contracts under a scoped integration user
Athe nightly rule job and the renewal alert job, credential store, change log
Aproposals and renewal alerts answered in one click
Aaccount, renewal and change questions answered from live CRM data
Aactivity-note summaries only, allow-listed model, EU region routing
Athe seller's identity behind every accepted proposal, so the CRM trail names a person
Athe hygiene score per team, published next to the pipeline it qualifies
Awhich corrections a robot may apply and which must be proposed
CIllustrative economic model
Numbers you can check against your own data.
The share the nightly job and the agent actually remove, 0.6, is folded into the volume rather than shown as its own line, so the calculator counts 119 seller-weeks a month instead of all 198, at 55 minutes and €57 an hour fully loaded. Revenue operations sits outside it: 60 hours a month, 0.7 automatable, is 42 hours at €39, roughly €19,700 a year, taking the combined pool to about €94,300. Where the case usually lies is unpriced: a forecast management can act on, renewals kept because somebody worked them early, new sellers ramping on records they trust. Nothing here was measured at a client.
Run the numbers on your data
An illustrative estimate from your own inputs. It models released capacity; it is not a promise of savings.
Business benefits
- Renewals are worked from ninety days out, because the alert reaches owner and manager instead of waiting for the customer to mention the date
- The pipeline the sales director presents is the one they believe, since stale and incomplete records are caught nightly rather than quarterly
- Sellers spend minutes accepting proposals instead of hours in clean-up campaigns, and get account answers without opening a queue
- Sales operations moves from help desk back to territory design, pricing and analysis
- New sellers inherit accounts with a readable history, because duplicates are merged and activity is summarised
- Anything added later, a scoring model, a forecasting tool, a sales assistant, learns from maintained data
The management view
- Pipeline and pipeline quality are read side by side: records corrected, proposals open per seller, which teams keep their data current
- Renewals become a managed list with owners, dates and a contact history rather than a recurring surprise
- Review meetings move from arguing about the data to discussing the deals, which is what the meeting was for
- Ownership is explicit and auditable: revenue operations owns the rules, sellers own their records, and the nightly job enforces the agreement
Board-level KPIs
Security and governance
Trust in automation is built on the audit trail, not on a promise.
- The robot signs in as a dedicated CRM integration user whose rights stop at the entities and fields named in the rule set, its secret held in the Orchestrator credential store or Azure Key Vault
- Every automatic change carries the rule behind it and the previous value, so it can be explained and reversed; merges and close-date changes never apply without the owner's answer
- Sellers respond under their own Microsoft Entra ID identity in Teams, so the CRM audit trail names the person who decided, not the robot
- The agent answers only from CRM data the asking user may see, through the AI Trust Layer with an allow-listed model, EU region routing and an audit record of prompts and tool calls
- Processing stays in the EU region of UiPath Automation Cloud and inside the Microsoft 365 EU Data Boundary; customer contact data goes no further than a query result
Why now
Sales teams are offered assistants and forecasting models that all assume the CRM is right, so data quality has stopped being a hygiene topic and become a precondition for the rest of the roadmap
Teams is where sellers already read and reply on a phone, which makes a one-click proposal realistic in a way the email clean-up campaign never was
Turnover in sales roles stays high; at the modelled numbers the seller and revenue-operations time alone is about €7,900 a month, and every departure leaves records that decay unless something watches them
Relevant executive roles
The pipeline number becomes defensible, and renewals are worked early instead of discovered late
Hiring, cash and what the board is told rest on a forecast built from maintained records, not recollection
The team stops running clean-up campaigns and owns a rule set that runs nightly
Capacity planning and delivery scheduling inherit CRM data, so cleaning it removes recurring surprises
Common questions and objections
It warns at data entry. It does not clean history, reconcile records that arrived through imports, chase stale close dates, fill missing fields or put the decision in front of the seller in Teams.
The robot changes only what the rules call safe and proposes everything else. Each change carries its rule and previous value, acceptance rates are reported per team, and the pilot runs with proposals only until sellers trust it.
Clean data migrates better than dirty data, and the rules and connectors move with you; the same rule set runs against Salesforce. Migrating unresolved duplicates pays for them twice.
When this is not the right solution
- A small CRM with a disciplined team and a manager who reviews records weekly; the rules would confirm what is already true
- No agreement on who owns which records: a proposal then has nobody to reach, and rules cannot enforce ownership that does not exist
- A sales team that does not work in Teams, since the mechanism depends on reaching people where they already read
A question for the next management meeting
Name the next ten renewals falling due here, with their owners and the date each was last discussed with the customer: how long would that take, and whom would we have to ask?
Implementation approach
A scope without ambiguity, before anything is signed.
We deliver
- A data-quality assessment on a CRM export, showing what each candidate rule would flag before anything is switched on
- The rule set and the safe-change boundary, agreed line by line with revenue operations and sales
- The nightly hygiene job, its change log and the proposal cards with one-click responses
- The renewal and milestone alert job, with windows and escalation to the manager
- The conversational agent: CRM tools, guardrails, entitlement scoping, evaluation set
- The Power BI hygiene score published beside the pipeline
- A pilot with proposals only, then safe corrections once acceptance rates justify them
We need from you
- A CRM sandbox and an integration user scoped to the entities and fields in the rules
- A revenue-operations owner who can decide thresholds and settle disputes about them
- Agreed record ownership, so a proposal always has somebody to go to
- An export of open opportunities and contracts, customer names removed if you prefer
Stages
Assessment
Candidate rules run against an export so thresholds are agreed on evidence, not opinion
Design
The rule set, the safe-change boundary, the card wording, the alert windows
Build
Nightly job, change log, proposal and renewal cards, the agent and its tools, the hygiene score
Validation
Rules replayed on historical records, cards reviewed by sellers, agent answers checked
Pilot
One region, proposals only, measured by acceptance rate not records touched
Rollout
Safe corrections enabled, remaining regions added, alert windows tuned
Departmental. Effort is driven by the state of the CRM and by how long the rules take to agree; the build is short once sales and revenue operations settle what a robot may change alone.
Eleven weeks to a renewal that exists only in a spreadsheet.
Export your open opportunities and contracts, customer names removed if you prefer. Within a week you get back how many are stale, duplicated or missing the fields your forecast depends on, and how many renewals fall in the next two quarters.
Cross out every close date in the pastThe neighbouring process usually has the same problem
The pipeline review starts with an argument about the data, not about the deals.
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